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Boedeker, Peter – Practical Assessment, Research & Evaluation, 2017
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…
Descriptors: Hierarchical Linear Modeling, Maximum Likelihood Statistics, Bayesian Statistics, Computation
Leckie, George – Journal of Educational and Behavioral Statistics, 2018
The traditional approach to estimating the consistency of school effects across subject areas and the stability of school effects across time is to fit separate value-added multilevel models to each subject or cohort and to correlate the resulting empirical Bayes predictions. We show that this gives biased correlations and these biases cannot be…
Descriptors: Value Added Models, Reliability, Statistical Bias, Computation
Dülmer, Hermann – Sociological Methods & Research, 2016
The factorial survey is an experimental design consisting of varying situations (vignettes) that have to be judged by respondents. For more complex research questions, it quickly becomes impossible for an individual respondent to judge all vignettes. To overcome this problem, random designs are recommended most of the time, whereas quota designs…
Descriptors: Factor Analysis, Reliability, Validity, Benchmarking
Martinkova, Patricia; Goldhaber, Dan – Center for Education Data & Research, 2015
Inter-rater reliability, commonly assessed by intra-class correlation coefficient ICC, is an important index for describing the extent to which there is consistency amongst two or more raters in assigned measures. In organizational research, the data structure is often hierarchical and designs deviate substantially from the ideal of a balanced…
Descriptors: Teacher Selection, Interrater Reliability, Public School Teachers, Hierarchical Linear Modeling
Hemmerechts, Kenneth; Agirdag, Orhan; Kavadias, Dimokritos – Educational Review, 2017
In this article, we explore the relationship between parental literacy activities with the child, socio-economic status (SES) and reading literacy. We draw upon the Bourdieusian theory of habitus development to explore this relationship. Multilevel analyses of a survey of 43,870 pupils (with an average age of 10 years) in 10 Western European…
Descriptors: Correlation, Socioeconomic Status, Elementary School Students, Literacy
Shapiro, Valerie B.; Kim, B. K. Elizabeth; Accomazzo, Sarah; Roscoe, Joe N. – International Journal of Emotional Education, 2016
"The Devereux Student Strengths Assessment Mini" (DESSA-Mini) (LeBuffe, Shapiro, & Naglieri, 2014) efficiently monitors the growth of Social-Emotional Competence (SEC) in the routine implementation of Social Emotional Learning programs. The DESSA-Mini is used to assess approximately half a million children around the world. Since…
Descriptors: Predictor Variables, Social Development, Emotional Development, School Districts
Adams, Curt M.; Olsen, Jentre J.; Ware, Jordan K. – Educational Administration Quarterly, 2017
Purpose: The purpose of this study was to define student learning capacity and to examine the role of the school principal in nurturing it. Method: The study used cross-sectional data from 3,175 students in 70 schools located in a metropolitan area of a Southwestern city. We tested three hypotheses by following a conventional modeling building…
Descriptors: Principals, Administrator Role, Hypothesis Testing, Student Needs
Aydin, Burak; Leite, Walter L.; Algina, James – Educational and Psychological Measurement, 2016
We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…
Descriptors: Error of Measurement, Predictor Variables, Randomized Controlled Trials, Experimental Groups
Peugh, James L. – Journal of Early Adolescence, 2014
Applied early adolescent researchers often sample students (Level 1) from within classrooms (Level 2) that are nested within schools (Level 3), resulting in data that requires multilevel modeling analysis to avoid Type 1 errors. Although several articles have been published to assist researchers with analyzing sample data nested at two levels, few…
Descriptors: Early Adolescents, Research, Hierarchical Linear Modeling, Data Analysis
Jiao, Hong; Wang, Shudong; He, Wei – Journal of Educational Measurement, 2013
This study demonstrated the equivalence between the Rasch testlet model and the three-level one-parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE)…
Descriptors: Computation, Item Response Theory, Models, Monte Carlo Methods
Jeon, Minjeong – ProQuest LLC, 2012
Maximum likelihood (ML) estimation of generalized linear mixed models (GLMMs) is technically challenging because of the intractable likelihoods that involve high dimensional integrations over random effects. The problem is magnified when the random effects have a crossed design and thus the data cannot be reduced to small independent clusters. A…
Descriptors: Hierarchical Linear Modeling, Computation, Measurement, Maximum Likelihood Statistics
Shin, Jihyung – ProQuest LLC, 2012
This research is motivated by an analysis of reading research data. We are interested in modeling the test outcome of ability to fluently recode letters into sounds of kindergarten children aged between 5 and 7. The data showed excessive zero scores (more than 30% of children) on the test. In this dissertation, we carefully examine the models…
Descriptors: Educational Research, Hierarchical Linear Modeling, Reading Research, Kindergarten